Mobile health (mHealth) programs utilize automated voice messages to deliver health information, particularly targeting underserved communities, demonstrating the effectiveness of using mobile technology to disseminate crucial health information to these populations, improving health outcomes through increased awareness and behavioral change. India's Kilkari program delivers vital maternal health information via weekly voice calls to millions of mothers. However, the current random call scheduling often results in missed calls and reduced message delivery. This study presents a field trial of a collaborative bandit algorithm designed to optimize call timing by learning individual mothers' preferred call times. We deployed the algorithm with around $6500$ Kilkari participants as a pilot study, comparing its performance to the baseline random calling approach. Our results demonstrate a statistically significant improvement in call pick-up rates with the bandit algorithm, indicating its potential to enhance message delivery and impact millions of mothers across India. This research highlights the efficacy of personalized scheduling in mobile health interventions and underscores the potential of machine learning to improve maternal health outreach at scale.

Are tech companies using your private data to train AI models? Leading tech companies are in a race to release and improve artificial intelligence (AI) products, leaving users in the United States to puzzle out how much of their personal data could be extracted to train AI tools. Meta (which owns Facebook, Instagram, Threads and WhatsApp), Google and LinkedIn have all rolled out AI app features that have the capacity to draw on users' public profiles or emails. Google and LinkedIn offer users ways to opt out of the AI features, while Meta's AI tool provides no means for its users to say "no, thanks." Anthropic's AI hacking claims divide experts Posts warned that the platforms' AI tool rollouts make most private information available for tech company harvesting .

Rod Stewart had a few surprise guests at a recent concert in Charlotte, North Carolina. His old friend Ozzy Osbourne, the lead singer of Black Sabbath who died last month, was apparently beamed in from some kind of rock heaven, where he was reunited with other departed stars including Michael Jackson, Tina Turner and Bob Marley. The AI-generated images divided Stewart's fans. Some denounced them as disrespectful and distasteful; others found the tribute beautiful. At about the same time, another AI controversy erupted when Jim Acosta, a former CNN White House correspondent, interviewed a digital recreation of Joaquin Oliver, who was killed at the age of 17 in a 2018 high school shooting in Florida.

An unsuspecting grandmother received a shock after Apple's AI left her an X-rated message. Louise Littlejohn, 66, from Dunfermline in Scotland, had received an innocuous voice message from a car dealership in Motherwell on Wednesday. But Apple's AI-powered Visual Voicemail tool – which gives users text transcriptions of voice calls – completely botched the transcription. The jumbled text left on her iPhone asked if she had'been able to have sex' and called her a'piece of s***'. Confusingly, it said: 'Just be told to see if you have received an invite on your car if you've been able to have sex.'

There was something strange about her voice, they thought. It was not unfamiliar but, after a while, it started to go all over the place. Science presenter Liz Bonnin's accent, as regular BBC viewers know, is Irish. But this voice message, ostensibly granting permission to use her likeness in an ad campaign, seemed to place her on the other side of the world. The message, it turns out, was a fake – AI-generated to mimic Bonnin's voice.

A New Jersey couple woke up to a 67-minute-long voicemail from an'unknown caller' - and discovered it was left by their Amazon Alexa. 'I was checking the message ... and was like, wait, this is me talking in the bedroom,' she said. Alexa can call your smartphone if you trigger the'Find My Phone' feature, but a company spokesperson said the Amazon Echo doesn't record or store conversations unless it hears the'wake word,' prompting a light on the device to turn on to let you know it's listening. Amazon has come under fire for its devices recording conversations and faced two separate privacy violation lawsuits last year, including a claim that it had violated children's privacy rights by refusing to remove the recording history of minors. A judge ruled that the company had to pay out a collective 30.8 million for both violations. 'There wasn't a lot of talking in the message, mostly bleeping,' Creegan said, but added that she could hear snippets of her telling Alexa to'turn the lights off' adding that there was'two or three sentences of me talking to the dog.

Voice messages, by nature, prevent users from gauging the emotional tone without fully diving into the audio content. This hinders the shared emotional experience at the pre-retrieval stage. Research scarcely explored "Emotional Teasers"-pre-retrieval cues offering a glimpse into an awaiting message's emotional tone without disclosing its content. We introduce EmoWear, a smartwatch voice messaging system enabling users to apply 30 animation teasers on message bubbles to reflect emotions. EmoWear eases senders' choice by prioritizing emotions based on semantic and acoustic processing. EmoWear was evaluated in comparison with a mirroring system using color-coded message bubbles as emotional cues (N=24). Results showed EmoWear significantly enhanced emotional communication experience in both receiving and sending messages. The animated teasers were considered intuitive and valued for diverse expressions. Desirable interaction qualities and practical implications are distilled for future design. We thereby contribute both a novel system and empirical knowledge concerning emotional teasers for voice messaging.

The widespread availability of cell phones has enabled non-profits to deliver critical health information to their beneficiaries in a timely manner. This paper describes our work to assist non-profits that employ automated messaging programs to deliver timely preventive care information to beneficiaries (new and expecting mothers) during pregnancy and after delivery. Unfortunately, a key challenge in such information delivery programs is that a significant fraction of beneficiaries drop out of the program. Yet, non-profits often have limited health-worker resources (time) to place crucial service calls for live interaction with beneficiaries to prevent such engagement drops. To assist non-profits in optimizing this limited resource, we developed a Restless Multi-Armed Bandits (RMABs) system. One key technical contribution in this system is a novel clustering method of offline historical data to infer unknown RMAB parameters. Our second major contribution is evaluation of our RMAB system in collaboration with an NGO, via a real-world service quality improvement study. The study compared strategies for optimizing service calls to 23003 participants over a period of 7 weeks to reduce engagement drops. We show that the RMAB group provides statistically significant improvement over other comparison groups, reducing ~ 30% engagement drops. To the best of our knowledge, this is the first study demonstrating the utility of RMABs in real world public health settings. We are transitioning our RMAB system to the NGO for real-world use.

WhatsApp is working on a feature that will provide written transcriptions of incoming voice messages. WABetaInfo posted screenshots of the alleged Transcribe feature, which includes disclaimers it is optional and users have to give permission for the app to access their phone's speech recognition software. The new feature raises questions about privacy, as calls will be sent to Apple for transcription and to help Apple'improve its speech recognition technology.' WhatsApp says the calls will remain protected by end-to-end encryption because they'won't be directly linked to your identity'. Previously, WhatsApp users had to rely on third-party apps to get transcriptions. The WhatsApp info site WABetaInfo shares images of a new voice message transcription feature coming to the popular messaging app.

If your home is kitted out with Amazon Echo devices, you can now use the "drop in" feature to talk to all of them at the same time. This essentially brings a quick and easy intercom to your home. Up until now, you could use Amazon's "drop in" feature to send a voice message to only one other Alexa-powered device. Let's say from the Amazon Echo in your living room to the Amazon Echo Dot in your kitchen. You could "drop in" then start a conversation that works both ways.